Description Usage Arguments Details Value

Runs through a model selection algorithm to determine the best model in a given set

1 2 3 | ```
rank.models(data, ..., nested = F, bootstrap = F, model.type = "ssm",
alpha = 0.05, robust = F, eff = 0.6, B = 50, G = 1e+05, freq = 1,
seed = 1337)
``` |

`data` |
A |

`...` |
Different |

`nested` |
A |

`bootstrap` |
A |

`model.type` |
A |

`alpha` |
A |

`robust` |
A |

`eff` |
A |

`B` |
A |

`G` |
A |

`freq` |
A |

`seed` |
A |

The models MUST be nested within each other. If the models are not nested, the algorithm creates the "common denominator" model.

To supply the models, enter them as: AR1()+WN(), AR1(), 3*AR1()

Any parameter that you wish to use must then be specified. e.g. to specify nested, you must use nested = T. Otherwise, it the function will stop.

Due to the structure of `rank.models`

, you cannot mix and match `AR1()`

and `GM()`

objects.
So you must enter either AR1() or GM() objects.

A `rank.models`

object.

gmwm documentation built on April 14, 2017, 4:38 p.m.

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